Acoustic measurements with the sine sweep method

Learn about this robust method for room acoustic measurements. **Press 'C' for subtitles. Para Español, active subtítulos y vaya a los ajustes.**
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0:00 Room acoustic measurements
0:44 Impulse, or Dirac signal
1:12 Impulse response
2:26 Problems with impulse stimuli
3:36 Sine sweep
4:35 Processing of recorded sweep
5:02 Summary
ODEON is a software for simulation and measurements of room acoustics, and is the preferred software by acoustic engineers and architectural consultancy firms. You can model sound sources ranging from point sources with directivities to large industrial machines, visualize acoustics with ray tracing, billiard balls, and color grids, and even listen to the simulated acoustics in your room with auralisations. ODEON is the optimum acoustic design tool when working with concert hall and auditorium acoustics, industrial and restaurant noise, and PA system design. The video tutorials in this channel will explain the basics of room acoustics analysis using ODEON.

[@MichaelWeizenfeld]

Hi! Nice video! I compared two methods in REW, and got slightly different results. My thoughts it is much easier for loudspeaker to play sweep tones instead of Dirac, so i think for fast sounds Dirac is more accurate in terms of possibilities of loudspeaker, and for more harmonic signal sweep tone is more accurate.

[@FKnox123]

What is the optimal duration of the sweep signal for a given bandwidth?

[@ODEONRoomAcousticsSoftware]

Hello! The recommended length would not depend so much on the bandwidth but on the SNR, so how much you are above the background noise. If your SNR is too low, that's when you increase the sweep length to increase the SNR

[@bendhamwatt]

This was awesome. However, I do have a question that I can't seem to find the answer to. As you stated the sine sweep is the "time stretching" of the dirac. That makes sense. But then that means when you then play the sine sweep, because it takes a while to emit the total sine sweep sound, then as the microphone get's to measuring the high frequency component of the sine sweep, this part of the recording must have lower freqeuncy reflections included in it because it took lets say 1 second before the 20 kHz sound was played. So then, how do you totally leave out the reflections from this analysis when you do the FFT? The impulse was easy to remove the reflections because it only had a length of sound that we know lasts a very very small amount of time, the sine sweep persists longer through time.

[@ODEONRoomAcousticsSoftware]

Hello! First, you apply a deconvolution filter, which basically shifts all frequencies back to start at the same time, and so the recording turns into an impulse response.
From the impulse response, if you take a single FFT of the whole thing even with reverberation tail, it still gives you a valid spectrum of the room. But it would be more accurate and informative to produce a spectrogram (using an STFT instead of an FFT) which then will also show how the different frequencies decay over time.

[@bendhamwatt]

@@ODEONRoomAcousticsSoftware ​ Ah, that makes sense. Very clever. That answers my question, I appreciate you reaching back.